Exploring perspectives, preferences and needs of a telemonitoring program for women at high risk for preeclampsia in a tertiary health facility of Karachi: a qualitative study protocol
Bibliographic record
Abstract
BACKGROUND: In Pakistan, deaths from preeclampsia/eclampsia (PE/E) represent one-third of maternal deaths reported at tertiary care hospitals. To reduce the morbidity and mortality associated with PE/E, an accessible strategy is to support pregnant women at high risk for preeclampsia (HRPE) by closely monitoring their blood pressures at home (i.e., telemonitoring) for the earliest signs of preeclampsia. This could lead to the earliest possible detection of high blood pressure, resulting in early intervention such as through medications, hospitalization, or delivery of the baby. The study aims to explore the perspectives, preferences and needs of telemonitoring (TM) for pregnant women at HRPE in Karachi, to inform future implementation strategies. METHODS: The study will employ an exploratory qualitative research design. The study will be conducted at the Jinnah Postgraduate Medical Centre (JPMC) hospital and Aga Khan University Hospital (AKUH) in Karachi, Sindh, Pakistan. Data will be collected through key-informant interviews (KIIs) and in-depth patient interviews (IDPIs). IDPIs will be conducted with the pregnant women at HRPE who are visiting the out-patient department/ antenatal clinics of JPMC hospital for antenatal check-ups and immunizations. KIIs will be conducted with the obstetricians, Maternal, neonatal and child health (MNCH) specialists and health care providers at JPMC, as well as TM experts from Karachi. Study data will be analyzed through conventional content analysis. Interviews are anticipated to begin in April 2020 and to be completed during the summer of 2020. DISCUSSION: This is the first study to explore the use of TM program for pregnant women at HRPE in a tertiary health facility in Karachi. The research will help explore perceived benefits associated with the use of a TM program alongside potential facilitators and barriers that may help inform the future implementation of a TM program for pregnant women at HRPE in Karachi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".